Modeling, multi-response optimization, and performance reliability of green metal composites produced from municipal wastes

For the purpose of reducing and reusing municipal wastes, used aluminum products, waste glass, and rice husk were selected and reprocessed into green-metal composite. The process entailed recycling of waste glass and rice husk into glass powder (GP) and rice husk ash (RHA), respectively. These were employed as additives in recycled aluminum melt. Composite samples development entailed group mixes A, B, C, and D. Group mix A was prepared by the blend of 3 wt.% RHA at constant proportion with 2, 4, 6, 8, and 10 wt.% GP. Regarding group mixes B, C, D, the same proportion of GP was blended with 6, 9, 12% RHA at constant dosage respectively. Mechanical properties; tensile, impact, flexural and compressive strengths, and fracture toughness were investigated. The significance of the additives on the composites was appraised via performance reliability index (PRI) as a measure of effective property based on variable experimental inputs. From the results, the commix of 3% RHA and 4, 6, 8% GP; 6% RHA and 2, 4, 6% GP; 9% RHA and 2, 4% GP exhibited enhancement of effective property. The compressive strength of the composites was showcased to be the most improved mechanical property. Maximum improvement was obtained at the collage of 4% GP and 6% RHA, yielding a PRI of 1.35. Results of the ANOVA revealed that the experimental inputs had significant contribution on each property response. Mathematical models were developed for each property response, and multi-response optimization predicted an optimum mix of 3.93 wt.% GP and 6.14% RHA. The difference between the property value of the predicted and confirmation experiment is < +/- 0.05, validating the models.